Medical QA

QA: Question Answering

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4 papers in the last four weeks, up 33% on the four weeks before. 0.0% of all new papers.

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Conditional Rank Allocation for Taxonomy-Aware Medical Language Model Adaptation
Oct 5, 2026Guangyuan Dong, Ziwei Hong, Xuehao Zhou +6Low-Rank Adaptation Domain Adaptation for LLMs
National University of Singapore, Singapore · University of Pennsylvania, USA · Department of Urology, Shanghai General Hospital, Shanghai, China +3
Jev in Medicine: A Benchmark Evaluation
Sep 27, 2026Alfredo Madrid-García, Beatriz Merino-BarbanchoMedical QA Clinical Reasoning
Independent researcher Madrid, Spain
CRISS: A Retrieval-Augmented AI Chatbot for Assisting Cancer Registrars
Sep 24, 2026Vani Seth, Mohammad Beheshti, Anirudh Kambhampati +4Retrieval-Augmented Generation Human-in-the-Loop AI
Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, USA · Missouri Cancer Registry and Research Center, Department of Public Health, College of Health Sciences, University of Missouri, Columbia, USA · MU Institute for Data Science and Informatics, University of Missouri, Columbia, USA
Rewarding Reasoning, Not Answers: Fixing and Bounding Test-Time Reinforcement Learning on Medical QA
Sep 15, 2026Kailong Fan, Anqi Pu, Yichen Wu +7Process Reward Models RL for Language Model Reasoning
1Harvard Medical School/MGH · 3Harvard University · 2Zhejiang University
Which Medical Questions Deserve Rationales? Perturbation-Sensitive Selection for Robust QA
Sep 9, 2026Yuexin Wu, Dayou Yu, Vasile RusData Selection Medical QA
Department of Computer Science, University of Memphis
Untangling the Mechanisms of Misleading Context in Medical Question Answering
Sep 2, 2026Robin Linzmayer, Noémie ElhadadMedical QA Language Model Robustness
Department of Computer Science, Columbia University, New York, NY, USA · Department of Biomedical Informatics, Columbia University, New York, NY, USA
ECGQuest: Benchmarking and Fine-Tuning Language Models for Electrocardiography
Aug 31, 2026Mohammadsina Hassannia, Matthew A. Reyna, Reza SameniElectrocardiography LLM Fine-Tuning
Department of Biomedical Informatics Emory University Atlanta, GA 30322, USA · Department of Biomedical Engineering Georgia Institute of Technology and Department of Biomedical Informatics Emory University Atlanta, GA 30332, USA
ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering
Aug 11, 2026Taojie Zhu, Yuan Xia, Tao Sun +8Rubric-Based RL Medical QA
Tsinghua University · Ant Group · Zhejiang University
Gaokerena: A Small Persian Medical Language Model Family
Aug 2, 2026Mehrdad Ghassabi, Hamidreza Baradaran Kashani, Pedram Rostami +5RL for Language Model Reasoning Small Language Models
University of Isfahan, Isfahan, Iran · University of Tehran, Tehran, Iran · University of Windsor, Windsor, ON, Canada +3
Bridging the English-Arabic Medical Knowledge Gap: Targeted Low-Rank Adaptation via Causal Layer Selection
Jul 31, 2026Chaimae Abouzahir, Musa Khan, Hala Ali-Hassan +7LLM Fine-Tuning Low-Rank Adaptation
New York University Abu Dhabi · Cleveland Clinic Abu Dhabi
MedLLM: An Open Medical Language Model at the Sub-Billion Scale
Jul 29, 2026Maxx Richard Rahman, Asim Ahmed, Mihan Mohagheghzadeh +1LLM Fine-Tuning Small Language Models
German Research Center for Artificial Intelligence (DFKI), Germany · Saarland University, Germany
MedJudgeRAG: Option-Wise Evidence Judgment with Dynamic Knowledge Graphs for Medical MCQA
Jul 24, 2026Seongwon Seo, Seung Hwan Cho, Young-Min KimGraph Retrieval-Augmented Generation Medical QA
Department of Industrial Data Engineering, Hanyang University, Seoul, South Korea · School of Interdisciplinary Industrial Studies, Hanyang University, Seoul, South Korea
Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering
Jun 30, 2026Hao Gong, Ruilin Gong, Yining HuangLow-Rank Adaptation Medical QA
University of Chinese Academy of Sciences · Henan University of Technology · Meta Emergence Laboratory
DEEPMED Search: An Open-Source Agentic Platform for Medical Deep Research with Introspective Verification
Jun 29, 2026Maolin Liu, Fanyu Xu, Ruoqing Xu +3LLM Answer Verification Agentic Search
School of Computer Science and Software Engineering, Shanghai University · Department of Computer Science and Engineering, Shanghai Jiao Tong University
mamabench and mamaretrieval: Benchmarks for Evaluating Medical Retrieval-Augmented Generation in Maternal, Neonatal, and Reproductive Health
Jun 28, 2026Yi RenHealthcare Medical QA
École Polytechnique Fédérale de Lausanne, Switzerland
TriageRA-CCF: Source-Side Clinical Confidence and Coverage Signals for Adaptive Rank Budgeting in Medical LLMs
Jun 28, 2026Shucan Ji, Yining Huang, Hongliang GuoLow-Rank Adaptation Medical QA
College of Computer Science, Sichuan University, Chengdu, China · Meta Emergence Laboratory
Trade-offs in Medical LLM Adaptation: An Empirical Study in French QA
Jun 17, 2026Ikram Belmadani, Oumaima El Khettari, Carlos Ramisch +3LLM Fine-Tuning Domain-Adaptive Pretraining
Aix-Marseille Univ., CNRS, LIS UMR 7020, 13000 Marseille, France · Nantes Univ., École Centrale Nantes, CNRS, LS2N UMR 6004, 44000 Nantes, France · Grenoble Alpes Univ., CNRS, INRIA, Grenoble INP, LIG UMR 5217, 38000 Grenoble, France
Let LLMs Judge Each Other: Multi-Agent Peer-Reviewed Reasoning for Medical Question Answering
Jun 13, 2026Zaifu Zhan, Shuang Zhou, Rui ZhangMulti-Agent LLM Systems LLM Answer Verification
Department of Electrical and Computer Engineering, University of Minnesota, 200 Union St SE, 55455, Minneapolis, MN, United States · Division of Computational Health Sciences, Department of Surgery, University of Minnesota, 420 Delaware St SE, 55455, Minneapolis, MN, United States
Semantic Reasoning in Medicine: The Role of Knowledge Graphs Across Five Key Domains
Jun 13, 2026Haniye Sherafatmandjoo, Mohammad Akbari, Zahed RahmatiKG Construction Healthcare
Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
ArogyaSutra: A Multi-Agent Framework for Multimodal Medical Reasoning in Indic Languages
Jun 11, 2026Tanmoy Kanti Halder, Akash Ghosh, Subhadip Baidya +2Multilingual Language Models RL for Language Model Reasoning
1Indian Institute of Technology Patna · 3Prasannadeb Women’s College · 2Indian Institute of Technology Kanpur
Measuring Epistemic Resilience of LLMs Under Misleading Medical Context
Jun 10, 2026Hongjian Zhou, Xinyu Zou, Jinge Wu +19LLM Reliability Medical QA
University of Oxford · University of Washington · University College London +1
Reassessing High-Performing LLMs on Polish Medical Exams: True Competence or Bias-Driven Performance?
Jun 10, 2026Antoni Lasik, Jakub Pokrywka, Łukasz Grzybowski +7LLM Evaluation LLM Reliability
NASK National Research Institute · Adam Mickiewicz University · ARAAI Poland +4
The Consistency Illusion: How Multi-Agent Debate Hides Reasoning Misalignment
Jun 7, 2026Xiaoyang Wang, Christopher C. YangLLM Agent Evaluation Multi-Agent Debate
1Drexel University
A Multi-modal Agentic Co-pilot for Evidence Grounded Computational Pathology
Jun 6, 2026Zhe Xu, Zhengyu Zhang, Zhiyuan Cai +12Computational Pathology Clinical Decision Support
Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China · Department of Pathology, Nanfang Hospital, Southern Medical University, Guangzhou, China · Department of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China +7
SurgiQ: A Large-Scale Multi-Domain Benchmark for Evaluating Surgical Understanding in Large Language Models
Jun 6, 2026Ayah Al-Naji, Edoardo Fazzari, Saif Alkindi +3LLM Evaluation Synthetic Benchmark Generation
Mohamed bin Zayed University of Artificial Intelligence, UAE
Severity-Aware Curriculum Learning with Multi-Model Response Selection for Medical Text Generation
Jun 3, 2026Ahmed Alansary, Molham Mohamed, Ali HamdiMedical QA Curriculum Learning
Faculty of Computer Science MSA University Giza, Egypt
Can I Take Another Dose? Evaluating LLM Decision-Making Under Temporal Uncertainty in OTC Dosing QA
Jun 2, 2026Maroof Kousar, Yibo HuTemporal Reasoning Medical QA
Illinois Institute of Technology Chicago, IL, USA
$M^3 QuestionIng$ : Multi-modal Multi-span Medical Question Answering
May 19, 2026Anisha Saha, Vaibhav Rathore, Abhisek Tiwari +3Medical VQA Multimodal QA
Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrucken, Germany · Indian Institute of Technology, Bombay, Mumbai, India · Clinical AI Assistance, Gurugram, India +2
Evaluating the Utility of Personal Health Records in Personalized Health AI
May 18, 2026Rory Sayres, Kejia Chen, Ayush Jain +19LLM Personalization Healthcare
1Google Research · †Work done while at Google Research
MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio
May 1, 2026Harshit Rajgarhia, Shuubham Ojha, Asif Shaik +4Audio QA Healthcare
Centific Global Solutions Inc. · University of Maryland, College Park, MD, USA.

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Conditional Rank Allocation for Taxonomy-Aware Medical Language Model Adaptation

Guangyuan Dong, Ziwei Hong, Xuehao Zhou, Zidong Yu+5

National University of Singapore, Singapore · University of Pennsylvania, USA · Department of Urology, Shanghai General Hospital, Shanghai, China+3

Low-Rank Adaptation Domain Adaptation for LLMs Medical QA Medical LLMs

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Medical question answering spans specialties and clinical operations that may benefit from different adaptation directions. We propose ARBOR, a parameter-efficient method that selects rank-one components from a shared low-rank basis for each question. An additive gate combines question representations, specialty tags, operation tags, and their interaction; a learned coefficient scales the adapter residual. An illustrative separation under orthogonal, equiprobable subtasks shows how conditional selection can avoid an approximation floor faced by a fixed update with the same active rank. This result motivates the design without asserting a corresponding bound for medical corpora. On Qwen3-8B across CMB, CMExam, MedQA, and MedMCQA, five-seed experiments yield 69.69% mean accuracy across benchmarks, exceeding LoRA r16 and MoELoRA by 1.26 and 1.30 percentage points, respectively. The reported advantage over LoRA r16 increases from 0.08 to 1.94 points as training expands from one to seven specialties. Tag perturbations and atom masking support the usefulness of clinical routing, while atom clusters align with the supplied specialty labels (adjusted Rand index 0.62). Calibration, transfer, and measured costs further characterize the method. These findings support structured conditional adaptation for medical QA, while leaving clinical safety and broader deployment untested.

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